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24 Repos

Awesome GitHub RepositoriesContext Compression

Techniques for summarizing data to maintain context window limits.

Distinguishing note: Focuses on AI memory management through summarization.

Explore 24 awesome GitHub repositories matching artificial intelligence & ml · Context Compression. Refine with filters or upvote what's useful.

Awesome Context Compression GitHub Repositories

Finde die besten Repos mit KI.Wir suchen mit KI nach den am besten passenden Repositories.
  • thedotmack/claude-memAvatar von thedotmack

    thedotmack/claude-mem

    82,698Auf GitHub ansehen↗

    Claude-mem is an agentic memory persistence system designed to provide AI assistants with long-term context across multiple development sessions. It functions as a background orchestrator that captures, summarizes, and indexes interaction history, allowing models to maintain continuity and recall technical decisions from past tasks. By utilizing a vector-augmented context engine, the system injects relevant historical observations into active sessions, ensuring that AI agents remain informed without exceeding finite token budgets. The project distinguishes itself through an endless memory arc

    Compresses tool observations into summaries to maintain linear context complexity.

    JavaScriptaiai-agentsai-memory
    Auf GitHub ansehen↗82,698
  • juliusbrussee/cavemanAvatar von JuliusBrussee

    JuliusBrussee/caveman

    73,390Auf GitHub ansehen↗

    Caveman is a set of tools and configurations designed for large language model token optimization. It focuses on reducing the amount of data processed during AI interactions to lower costs and maximize the available context window. The project implements a fragmented communication style that replaces full grammatical sentences with concise technical keywords. This approach extends to AI context optimization by condensing memory files and tool descriptions, and includes a specialized configuration for generating terse, one-line code reviews and short conventional commit messages. The system i

    Condenses project documentation and memory files to fit more relevant information into the AI context window.

    JavaScriptaianthropiccaveman
    Auf GitHub ansehen↗73,390
  • microsoft/ai-agents-for-beginnersAvatar von microsoft

    microsoft/ai-agents-for-beginners

    67,369Auf GitHub ansehen↗

    This project is a structured educational resource and technical guide for designing and implementing autonomous systems using large language models. It provides a comprehensive curriculum and code samples focused on agentic design patterns, autonomous development, and the creation of systems capable of planning and executing multi-step tasks. The resource details the implementation of agentic retrieval-augmented generation, where models autonomously plan and refine data searches. It covers a wide array of orchestrators and design patterns, including metacognitive reflection for self-correctin

    Implements techniques for summarizing conversation history to reduce token usage and prevent model distraction.

    Jupyter Notebookagentic-aiagentic-frameworkagentic-rag
    Auf GitHub ansehen↗67,369
  • chopratejas/headroomAvatar von chopratejas

    chopratejas/headroom

    29,537Auf GitHub ansehen↗

    Headroom is an AI gateway proxy and token optimizer designed to reduce the cost and latency of large language model interactions. It functions as an intermediary that intercepts traffic between clients and providers to apply context compression, request routing, and format translation. The system differentiates itself through a Model Context Protocol server implementation that delivers compression and retrieval tools to compatible AI hosts. It employs a content-aware compression pipeline and tiered importance scoring to trim redundant data from logs and tool outputs while preserving essential

    Maintains a compressed state of information shared across multiple agents to optimize memory usage.

    Pythonagentaianthropic
    Auf GitHub ansehen↗29,537
  • agentscope-ai/agentscopeAvatar von agentscope-ai

    agentscope-ai/agentscope

    26,895Auf GitHub ansehen↗

    Agentscope is a comprehensive toolkit for developing and orchestrating autonomous multi-agent systems. It provides a unified framework for building agents that can reason, execute tools, and manage memory, enabling the creation of complex, collaborative workflows where multiple specialized agents interact to solve multi-step objectives. The platform distinguishes itself through a robust orchestration engine that supports both sequential and concurrent agent pipelines. It utilizes a centralized event bus for real-time telemetry, allowing developers to track agent reasoning, tool usage, and sys

    Summarizes conversation history to maintain context within token limits.

    Pythonagentchatbotlarge-language-models
    Auf GitHub ansehen↗26,895
  • rohitg00/agentmemoryAvatar von rohitg00

    rohitg00/agentmemory

    23,785Auf GitHub ansehen↗

    AgentMemory is a persistent knowledge store and memory server designed to provide AI coding agents with long-term memory. It functions as a knowledge graph engine and vector database store that saves and recalls project context, architectural decisions, and patterns across different sessions. The system distinguishes itself by using a tiered-memory consolidation pipeline that compresses raw observations into episodic, semantic, and procedural layers to optimize token usage. It employs a hybrid retrieval strategy combining keyword matching, vector embeddings, and graph traversal to surface rel

    Compresses observations and injects relevant context into the agent's prompt based on the available token budget.

    TypeScriptagentmemoryagentsai
    Auf GitHub ansehen↗23,785
  • forem/foremAvatar von forem

    forem/forem

    22,726Auf GitHub ansehen↗

    Forem is an open-source platform designed for building and managing technical communities. It functions as a social publishing engine that enables members to share long-form content, participate in threaded discussions, and engage through social interactions. The platform provides tools for organizations to maintain branded profiles, host community hackathons, and facilitate collaborative learning through structured educational tracks. Beyond its social features, Forem integrates advanced capabilities for AI agent workflow orchestration and codebase knowledge graphing. It allows developers to

    Summarizes data to maintain context window limits by stripping redundant content before transmission to language models.

    Rubycommunitydiscussionfeedback
    Auf GitHub ansehen↗22,726
  • claude-code-best/claude-codeAvatar von claude-code-best

    claude-code-best/claude-code

    20,272Auf GitHub ansehen↗

    Claude Code is a command-line interface and multi-agent orchestration framework designed for autonomous software engineering. It enables AI agents to perform codebase modifications, debugging, and Git workflow management while coordinating multiple specialized agents to decompose and execute complex engineering tasks in parallel. The system distinguishes itself through a high degree of isolation and safety, utilizing Git worktrees to create independent working directories for concurrent agents and implementing a tiered permission system that combines user rules, project policies, and OS-level

    Reactively reduces conversation history via summarization and truncation as the model's token limit is approached.

    TypeScript
    Auf GitHub ansehen↗20,272
  • github/docsAvatar von github

    github/docs

    18,951Auf GitHub ansehen↗

    GitHub Copilot is an AI-powered development platform designed to integrate large language models directly into coding environments. It functions as an interactive assistant and an agentic workflow orchestrator, enabling developers to automate code generation, perform automated code reviews, and execute complex, multi-step development tasks through natural language prompts. The platform distinguishes itself through its autonomous agent capabilities, which allow for repository-level research, implementation planning, and code modifications across multiple files. It supports a modular architectu

    Summarizes and compacts historical interaction data to maintain long-running session continuity within model context windows.

    TypeScriptdocsworks-with-codespaces
    Auf GitHub ansehen↗18,951
  • camel-ai/camelAvatar von camel-ai

    camel-ai/camel

    17,253Auf GitHub ansehen↗

    This project is a comprehensive framework for building and managing autonomous agent systems. It provides a unified architecture for orchestrating multi-agent societies, where specialized agents collaborate through roleplay to decompose and solve complex tasks. The system integrates language models with external environments, enabling agents to perform real-world actions through a standardized tool-calling abstraction layer. The framework distinguishes itself through its focus on iterative reasoning and data reliability. It employs automated feedback loops to refine agent outputs and self-eva

    Compresses long chat logs into concise summaries to maintain manageable context windows.

    Pythonagentai-societiesartificial-intelligence
    Auf GitHub ansehen↗17,253
  • lllyasviel/framepackAvatar von lllyasviel

    lllyasviel/FramePack

    17,028Auf GitHub ansehen↗

    FramePack is a neural video synthesis engine and generation framework designed to produce long, temporally consistent video sequences. It functions as a diffusion model optimizer, providing a suite of techniques to manage the computational demands of high-parameter video models while maintaining visual stability during extended generation tasks. The system distinguishes itself through a hierarchical approach to frame prediction, which plans distant anchor frames before filling in intermediate content to prevent cumulative temporal drift. By utilizing constant-length context compression and to

    Implements context compression to maintain memory efficiency during long-form video generation.

    Python
    Auf GitHub ansehen↗17,028
  • nesquena/hermes-webuiAvatar von nesquena

    nesquena/hermes-webui

    14,912Auf GitHub ansehen↗

    Hermes-webui is a self-hosted AI orchestrator and web interface for managing autonomous agents. It serves as a multi-provider gateway that connects cloud and local large language models, providing a central hub to execute scheduled background jobs, run shell commands, and manage agent memory on private hardware. The system distinguishes itself through a persistent memory manager that utilizes knowledge graphs and markdown files for long-term context across sessions. It features a model context protocol host for extending agent capabilities with standardized tools and supports the orchestratio

    Summarizes long conversation histories to keep the context within the model's token limits.

    Pythonagentai-agentshermes
    Auf GitHub ansehen↗14,912
  • lsdefine/genericagentAvatar von lsdefine

    lsdefine/GenericAgent

    13,017Auf GitHub ansehen↗

    GenericAgent is an LLM agent framework and autonomous system controller designed to manage local systems, web browsers, and hardware interfaces through action and observation loops. It functions as a tool orchestrator that routes model calls to local executors, enabling the automation of complex tasks on a host machine. The project is distinguished by its self-evolving AI agent capabilities, which convert successful execution paths into reusable procedural scripts and skill trees to reduce future reasoning overhead. It employs a context optimization engine that utilizes layered memory hierarc

    Reduces token usage by truncating tool returns, compressing historical rounds, and removing unnecessary messages.

    Pythonai-agentautomationautonomous-agent
    Auf GitHub ansehen↗13,017
  • chenhg5/cc-connectAvatar von chenhg5

    chenhg5/cc-connect

    12,915Auf GitHub ansehen↗

    cc-connect is an AI agent messaging bridge and session manager that connects local AI coding agents to third-party messaging platforms. It acts as a multimodal AI chat relay and a OneBot protocol gateway, allowing users to control local AI agents remotely via a variety of chat interfaces. The project distinguishes itself by providing a remote AI agent controller that enables the management of agents through slash commands and a web management dashboard. It supports multi-tenant project orchestration and session-based context isolation, ensuring that independent conversation threads are mainta

    Reduces token consumption by compacting the active conversation context window.

    Go
    Auf GitHub ansehen↗12,915
  • sanbuphy/learn-coding-agentAvatar von sanbuphy

    sanbuphy/learn-coding-agent

    12,034Auf GitHub ansehen↗

    This project is a framework for building AI coding agents that automate software development tasks using large language models. It includes a task lifecycle manager that tracks complex development goals through a persistent graph of dependent tasks and a system for multi-agent orchestration to delegate tasks to specialized sub-agents. The framework implements a Model Context Protocol client to discover and execute tools from external servers and provides a remote development bridge to synchronize local command line interfaces with remote containers or desktop environments. The system covers

    Reduces token usage by implementing a multi-layer strategy for summarizing conversation history and trimming stale markers.

    Auf GitHub ansehen↗12,034
  • langchain-ai/open_deep_researchAvatar von langchain-ai

    langchain-ai/open_deep_research

    11,719Auf GitHub ansehen↗

    Open Deep Research is an artificial intelligence framework designed to automate complex, multi-step research workflows. It functions as an autonomous agent that performs iterative web searches, analyzes retrieved data, and synthesizes information into structured reports. By decomposing broad queries into smaller sub-tasks, the system builds a comprehensive knowledge base to address open-ended questions. The platform distinguishes itself through an agentic loop that dynamically refines research strategies based on previous findings. It manages long-form data by compressing and summarizing cont

    Compresses and summarizes long-form research data to maintain information density within model context limits.

    Python
    Auf GitHub ansehen↗11,719
  • qodo-ai/pr-agentAvatar von qodo-ai

    qodo-ai/pr-agent

    11,630Auf GitHub ansehen↗

    PR Agent is an AI-powered code analysis tool and pull request reviewer that uses large language models to automate version control workflows. It functions as a programmatic agent that integrates with version control platforms to provide automated quality checks, explain code changes, and manage pull request documentation. The system distinguishes itself by enforcing organizational engineering standards through a customizable rule-based system. It leverages retrieval-augmented generation to inject repository context and organizational guidelines into its analysis, ensuring that feedback remain

    Implements techniques to shrink large file patches to fit within language model token limits.

    Pythoncode-reviewcodereviewcoding-assistant
    Auf GitHub ansehen↗11,630
  • cloudwego/einoAvatar von cloudwego

    cloudwego/eino

    9,675Auf GitHub ansehen↗

    Eino is an AI agent development kit and LLM application framework designed for building autonomous agents and orchestrating complex language model workflows. It serves as a multi-agent orchestration engine and workflow orchestrator, providing a graph-based execution model to route data between models, tools, and retrievers. The framework distinguishes itself through a robust set of multi-agent coordination patterns, including supervisor-led management, sequential flows, and autonomous reasoning loops like ReAct. It features advanced agent execution controls such as active turn preemption, che

    Implements summarization of old messages to keep dialogue history within the model's token limits.

    Goaiai-applicationai-framework
    Auf GitHub ansehen↗9,675
  • gsd-build/gsd-2Avatar von gsd-build

    gsd-build/gsd-2

    7,740Auf GitHub ansehen↗

    This project is an autonomous AI software development framework designed to plan, code, test, and commit software milestones without human intervention. It functions as a state-machine-driven agent loop that orchestrates development through a recurring cycle of research, execution, and verification. The system distinguishes itself through a git-isolated task runner that executes milestones in separate worktrees and branches, ensuring changes are squash-merged into a linear commit history. It features a multi-model routing gateway that assigns different LLM providers to specific workflow phase

    Reduces token consumption and manages memory by compressing context windows through a preference-driven pipeline.

    TypeScriptcontext-engineeringmeta-promptingspec-driven-development
    Auf GitHub ansehen↗7,740
  • phodal/auto-devAvatar von phodal

    phodal/auto-dev

    4,508Auf GitHub ansehen↗

    auto-dev ist ein KI-natives Software-Engineering-Tool und eine Multi-Agenten-Entwicklungsplattform, die darauf ausgelegt ist, den gesamten Softwareentwicklungslebenszyklus zu automatisieren. Es fungiert als autonomer Orchestrator, der KI-gesteuertes Coding, Testen und Infrastrukturkonfiguration durch deklarative Agentenketten verwaltet. Das Projekt basiert auf einem Kotlin-Multiplatform-KI-Framework, wodurch Agentenlogik in verschiedenen Umgebungen und auf unterschiedlichen Geräteschnittstellen ausgeführt werden kann. Die Plattform implementiert das Model Context Protocol, um Tools und Projektinformationen mit externen KI-Diensten auszutauschen. Sie zeichnet sich durch die Verwendung einer Retrieval-Augmented-Generation-Pipeline und baumbasiertem Code-Graphing aus, die abstrakte Syntaxbäume und Aufrufketten analysieren, um den Projektkontext zu komprimieren und Halluzinationen zu reduzieren. Eine interaktive Entwicklungsumgebung bietet Echtzeitsynchronisation von UML-Diagrammen, OpenAPI-Spezifikationen und Code-Diffs. Die Funktionsbereiche decken autonome Softwareentwicklung ab, einschließlich dynamischer Aufgabenplanung, iterativer testgetriebener Reparatur und Migration von Legacy-Code. Das System handhabt zudem Infrastructure-as-Code-Automatisierung für Docker- und CI/CD-Konfigurationen, KI-gestützte Code-Reviews sowie die Koordination geteilter KI-Personas und Prompt-Spezifikationen über Teams hinweg. Die Kernlogik ist in Kotlin Multiplatform implementiert, um eine konsistente plattformübergreifende Agentenbereitstellung sicherzustellen.

    Optimizes project context for complex refactoring tasks using a tree-based code graph engine.

    Kotlinaigcgenaigenaistack
    Auf GitHub ansehen↗4,508
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Unter-Tags erkunden

  • Compression ProxiesIntermediary services that compress payloads in real-time before they reach the AI model. **Distinct from Context Compression:** Specific to the proxy architectural pattern rather than just the compression technique.
  • Shared State OptimizationTechniques for maintaining and sharing compressed context across multiple AI agents. **Distinct from Context Compression:** Distinct from Context Compression: specifically focuses on the sharing and synchronization of compressed state across multiple agents.
  • Tree-Based CompressionUsing abstract syntax trees and call graphs to compress codebase context for LLM windows. **Distinct from Context Compression:** Distinct from general Context Compression by specifically using tree-based code graphing for structural project analysis.